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Questo corso ti offre un riepilogo dell'architettura encoder-decoder, che è un'architettura di machine learning potente e diffusa per attività da sequenza a sequenza come traduzione automatica, riassunto del testo e risposta alle domande. Apprenderai i componenti principali dell'architettura encoder-decoder e come addestrare e fornire questi modelli. Nella procedura dettagliata del lab corrispondente, implementerai in TensorFlow dall'inizio un semplice codice dell'architettura encoder-decoder per la generazione di poesie da zero.
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Syllabus
Architettura encoder-decoder: panoramica
Questo modulo ti offre un riepilogo dell'architettura encoder-decoder, che è un'architettura di machine learning potente e diffusa per attività da sequenza a sequenza come traduzione automatica, riassunto del testo e risposta alle domande. Apprenderai i componenti principali dell'architettura encoder-decoder e come addestrare e fornire questi modelli. Nella procedura dettagliata del lab corrispondente, implementerai in TensorFlow dall'inizio un semplice codice dell'architettura encoder-decoder per la generazione di poesie da zero.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops an understanding of encoder-decoder architectures, which are commonly used for natural language processing tasks such as machine translation and text summarization
Provides hands-on experience implementing an encoder-decoder architecture in TensorFlow for poetry generation, giving learners practical skills in deep learning
Taught by Google Cloud Training, a reputable organization known for its expertise in cloud computing and machine learning technologies
Suitable for learners with some background in machine learning and deep learning, particularly those interested in natural language processing
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Encoder-Decoder Architecture - Italiano with these
activities:
TensorFlow Tutorial
Show steps
Gain hands-on experience with TensorFlow, the framework used in the lab detailed in the course.
Browse courses on
TensorFlow
Show steps
-
Follow official TensorFlow tutorials to set up the environment and learn basic operations.
-
Build and train simple neural networks using TensorFlow's high-level Keras API.
Deep Learning with Python
Show steps
Expand your knowledge of deep learning, a foundational concept for encoder-decoder architectures.
View
Deep Learning with Python, Second Edition
on Amazon
Show steps
-
Read and study the book, focusing on chapters relevant to deep learning concepts.
-
Complete exercises and assignments provided in the book to reinforce your understanding.
Machine Learning Drills
Show steps
Practice foundational machine learning concepts and techniques to strengthen your understanding of encoder-decoder architectures.
Browse courses on
Machine Learning
Show steps
-
Solve supervised learning problems using linear regression and logistic regression.
-
Implement and train simple neural networks for binary classification and regression tasks.
-
Explore and experiment with different loss functions and optimization algorithms.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Study Group Discussions
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Engage in peer discussions to clarify concepts, share insights, and enhance understanding of encoder-decoder architectures.
Browse courses on
Encoder-Decoder Architecture
Show steps
-
Join or form a study group with classmates.
-
Discuss course materials, ask questions, and exchange ideas on a regular basis.
Encoder-Decoder Poem Generator
Show steps
Build a functional encoder-decoder model for generating creative text, specifically poetry.
Browse courses on
Encoder-Decoder Architecture
Show steps
-
Gather and preprocess a dataset of poems.
-
Define and implement an encoder model to convert poems into fixed-length vectors.
-
Design and implement a decoder model to generate poems from the encoded vectors.
-
Train and evaluate the encoder-decoder model on the poetry dataset.
Contribute to OpenNLP
Show steps
Gain practical experience and contribute to the broader machine learning community by participating in OpenNLP, a widely used NLP library.
Browse courses on
Natural Language Processing
Show steps
-
Identify an area within OpenNLP where you can contribute, based on your skills and interests.
-
Join the OpenNLP community and connect with other contributors.
-
Implement bug fixes, enhancements, or new features to the OpenNLP library.
-
Collaborate with other contributors and receive feedback on your contributions.
Encoder-Decoder Architecture Presentation
Show steps
Solidify your understanding of encoder-decoder architectures by presenting your knowledge to an audience.
Browse courses on
Encoder-Decoder Architecture
Show steps
-
Prepare a presentation that covers the key components and applications of encoder-decoder architectures.
-
Deliver the presentation to classmates or a wider audience.
-
Facilitate a discussion and answer questions about encoder-decoder architectures.
TensorFlow Tutorial
Show steps
Gain hands-on experience with TensorFlow, the framework used in the lab detailed in the course.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Follow official TensorFlow tutorials to set up the environment and learn basic operations.
- Build and train simple neural networks using TensorFlow's high-level Keras API.
Deep Learning with Python
Show steps
Expand your knowledge of deep learning, a foundational concept for encoder-decoder architectures.
View
Deep Learning with Python, Second Edition
on Amazon
Show steps
Show steps
Show steps
- Read and study the book, focusing on chapters relevant to deep learning concepts.
- Complete exercises and assignments provided in the book to reinforce your understanding.
Machine Learning Drills
Show steps
Practice foundational machine learning concepts and techniques to strengthen your understanding of encoder-decoder architectures.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Solve supervised learning problems using linear regression and logistic regression.
- Implement and train simple neural networks for binary classification and regression tasks.
- Explore and experiment with different loss functions and optimization algorithms.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Study Group Discussions
Show steps
Engage in peer discussions to clarify concepts, share insights, and enhance understanding of encoder-decoder architectures.
Browse courses on
Encoder-Decoder Architecture
Show steps
Show steps
Show steps
- Join or form a study group with classmates.
- Discuss course materials, ask questions, and exchange ideas on a regular basis.
Encoder-Decoder Poem Generator
Show steps
Build a functional encoder-decoder model for generating creative text, specifically poetry.
Browse courses on
Encoder-Decoder Architecture
Show steps
Show steps
Show steps
- Gather and preprocess a dataset of poems.
- Define and implement an encoder model to convert poems into fixed-length vectors.
- Design and implement a decoder model to generate poems from the encoded vectors.
- Train and evaluate the encoder-decoder model on the poetry dataset.
Contribute to OpenNLP
Show steps
Gain practical experience and contribute to the broader machine learning community by participating in OpenNLP, a widely used NLP library.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Identify an area within OpenNLP where you can contribute, based on your skills and interests.
- Join the OpenNLP community and connect with other contributors.
- Implement bug fixes, enhancements, or new features to the OpenNLP library.
- Collaborate with other contributors and receive feedback on your contributions.
Encoder-Decoder Architecture Presentation
Show steps
Solidify your understanding of encoder-decoder architectures by presenting your knowledge to an audience.
Browse courses on
Encoder-Decoder Architecture
Show steps
Show steps
Show steps
- Prepare a presentation that covers the key components and applications of encoder-decoder architectures.
- Deliver the presentation to classmates or a wider audience.
- Facilitate a discussion and answer questions about encoder-decoder architectures.
Career center
Learners who complete Encoder-Decoder Architecture - Italiano will develop knowledge and skills
that may be useful to these careers:
Ricercatore di Intelligenza Artificiale
Ricercatore di Intelligenza Artificiale
Un Ricercatore di Intelligenza Artificiale sviluppa nuovi algoritmi di machine learning, tecniche e modelli per risolvere problemi del mondo reale. Questo corso può aiutare a costruire una solida base nei concetti di base dell'architettura encoder-decoder, che è fondamentale per comprendere e sviluppare modelli di machine learning avanzati. La comprensione di questa architettura può aiutare i Ricercatori di Intelligenza Artificiale a creare modelli più efficaci e accurati per un'ampia gamma di applicazioni.
Scienziato dei Dati
Scienziato dei Dati
Uno Scienziato dei Dati utilizza tecniche di machine learning per estrarre informazioni dai dati. Questo corso può fornire una comprensione approfondita dell'architettura encoder-decoder, che è ampiamente utilizzata nella traduzione automatica e nel riassunto del testo. Questa conoscenza può aiutare gli Scienziati dei Dati a sviluppare soluzioni più sofisticate per l'elaborazione del linguaggio naturale e altre attività di analisi dei dati.
Ingegnere del Software
Ingegnere del Software
Un Ingegnere del Software progetta, sviluppa e mantiene applicazioni software. Questo corso può fornire una base nell'architettura encoder-decoder, che è un componente essenziale di molti sistemi di elaborazione del linguaggio naturale. Questa conoscenza può aiutare gli Ingegneri del Software a sviluppare applicazioni più robuste e scalabili che possono gestire attività complesse di elaborazione del linguaggio.
Analista di Ricerca Operativa
Analista di Ricerca Operativa
Un Analista di Ricerca Operativa utilizza tecniche di modellazione matematica per risolvere problemi aziendali. Questo corso può fornire una comprensione dei concetti di base dell'architettura encoder-decoder, che può essere utilizzata per sviluppare modelli per ottimizzare i processi aziendali e prendere decisioni migliori.
Architetto IT
Architetto IT
Un Architetto IT progetta e implementa soluzioni IT per le organizzazioni. Questo corso può fornire una panoramica dell'architettura encoder-decoder, che può essere utilizzata per progettare e implementare sistemi di elaborazione del linguaggio naturale in ambito aziendale. Questa conoscenza può aiutare gli Architetti IT a creare soluzioni più efficienti ed efficaci per le esigenze aziendali.
Manager di Prodotto
Manager di Prodotto
Un Manager di Prodotto gestisce lo sviluppo e il lancio di nuovi prodotti o funzionalità. Questo corso può fornire una comprensione di alto livello dell'architettura encoder-decoder, che può essere utile per comprendere le funzionalità e i limiti dei prodotti e delle funzionalità basati sul machine learning. Questa conoscenza può aiutare i Manager di Prodotto a prendere decisioni migliori sul lancio e la promozione di questi prodotti.
Analista Business Intelligence
Analista Business Intelligence
Un Analista Business Intelligence utilizza i dati per aiutare le aziende a prendere decisioni migliori. Questo corso può fornire una panoramica dei concetti di base dell'architettura encoder-decoder, che può essere utilizzata per analizzare i dati del linguaggio e identificare tendenze e modelli. Questa conoscenza può aiutare gli Analisti Business Intelligence a fornire informazioni più approfondite e preziose alle loro organizzazioni.
Tecnico di Supporto IT
Tecnico di Supporto IT
Un Tecnico di Supporto IT fornisce supporto tecnico a utenti e organizzazioni. Questo corso può fornire una comprensione di base dell'architettura encoder-decoder, che può essere utile per comprendere e risolvere problemi relativi a sistemi di elaborazione del linguaggio. Questa conoscenza può aiutare i Tecnici di Supporto IT a fornire un supporto più efficace agli utenti che utilizzano applicazioni basate sul machine learning.
For more career information including salaries, visit:
OpenCourser.com/course/an6y14/encoder
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Encoder-Decoder Architecture - Italiano.
Provides a comprehensive overview of neural machine translation, a popular deep learning technique for machine translation.
Provides a comprehensive overview of deep learning models for NLP, including encoder-decoders. It covers various NLP tasks and provides detailed explanations of how deep learning models can be applied to solve them. This book good reference for learning about the theoretical foundations of NLP using deep learning.
Provides a comprehensive overview of statistical machine translation, a popular machine learning technique for machine translation.
Provides a practical guide to deep learning using the Python programming language.
Provides a practical guide to deep learning using the Fastai and PyTorch libraries. It covers various deep learning models, including encoder-decoders, and provides hands-on examples of how to build and train these models using Python.
Provides a comprehensive overview of deep learning techniques for natural language processing. It covers various models, including encoder-decoders, and their applications in NLP tasks such as machine translation, text summarization, and question answering.
Provides a comprehensive overview of the Natural Language Toolkit (NLTK), a popular Python library for natural language processing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/an6y14/encoder
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Level
Advanced
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Transcript
Italiano
Good to know
Develops an understanding of encoder-decoder architectures, which are commonly used for natural language processing tasks such as machine translation and text summarization
Provides hands-on experience implementing an encoder-decoder architecture in TensorFlow for poetry generation, giving learners practical skills in deep learning
Taught by Google Cloud Training, a reputable organization known for its expertise in cloud computing and machine learning technologies
Suitable for learners with some background in machine learning and deep learning, particularly those interested in natural language processing
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